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There is mounting evidence that aerobic exercise has a positive effect on cognitive functions in older adults. To date, little is known about the neurometabolic and molecular mechanisms underlying this positive effect. The present study used magnetic resonance spectroscopy and quantitative MRI to systematically explore the effects of physical activity on human brain metabolism and grey matter (GM) volume in healthy aging. This is a randomised controlled assessor-blinded two-armed trial (n=53) to explore exercise-induced neuroprotective and metabolic effects on the brain in cognitively healthy older adults. Participants (age >65) were allocated to a 12-week individualised aerobic exercise programme intervention (n=29) or a 12-week waiting control group (n=24). The main outcomes were the change in cerebral metabolism and its association to brain-derived neurotrophic factor (BDNF) levels as well as changes in GM volume. We found that cerebral choline concentrations remained stable after 12 weeks of aerobic exercise in the intervention group, whereas they increased in the waiting control group. No effect of training was seen on cerebral N-acetyl-aspartate concentrations, nor on markers of neuronal energy reserve or BDNF levels. Further, we observed no change in cortical GM volume in response to aerobic exercise. The finding of stable choline concentrations in the intervention group over the 3 month period might indicate a neuroprotective effect of aerobic exercise. Choline might constitute a valid marker for an effect of aerobic exercise on cerebral metabolism in healthy aging.
Quantitative T1 mapping indicates tumor infiltration beyond the enhancing part of glioblastomas
(2019)
The aim of this study was to evaluate whether maps of quantitative T1 (qT1) differences induced by a gadolinium‐based contrast agent (CA) are better suited than conventional T1‐weighted (T1w) MR images for detecting infiltration inside and beyond the peritumoral edema of glioblastomas. Conventional T1w images and qT1 maps were obtained before and after gadolinium‐based CA administration in 33 patients with glioblastoma before therapy. The following data were calculated: (i) absolute qT1‐difference maps (qT1 pre‐CA ‐ qT1 post‐CA), (ii) relative qT1‐difference maps, (iii) absolute and (iv) relative differences of conventional T1w images acquired pre‐ and post‐CA. The values of these four datasets were compared in four different regions: (a) the enhancing tumor, (b) the peritumoral edema, (c) a 5 mm zone around the pathology (defined as the sum of regions a and b), and (d) the contralateral normal appearing brain tissue. Additionally, absolute qT1‐difference maps (displayed with linear gray scaling) were visually compared with respective conventional difference images. The enhancing tumor was visible both in the difference of conventional pre‐ and post‐CA T1w images and in the absolute qT1‐difference maps, whereas only the latter showed elevated values in the peritumoral edema and in some cases even beyond. Mean absolute qT1‐difference values were significantly higher (P < 0.01) in the enhancing tumor (838 ± 210 ms), the peritumoral edema (123 ± 74 ms) and in the 5 mm zone around the pathology (81 ± 31 ms) than in normal appearing tissue (32 ± 35 ms). In summary, absolute qT1‐difference maps—in contrast to the difference of T1w images—of untreated glioblastomas appear to be able to visualize CA leakage, and thus might indicate tumor cell infiltration in the edema region and beyond. Therefore, the absolute qT1‐difference maps are potentially useful for treatment planning.
The detection of cortical malformations in conventional MR images can be challenging. Prominent examples are focal cortical dysplasias (FCD), the most common cause of drug‐resistant focal epilepsy. The two main MRI hallmarks of cortical malformations are increased cortical thickness and blurring of the gray (GM) and white matter (WM) junction. The purpose of this study was to derive synthetic anatomies from quantitative T1 maps for the improved display of the above imaging characteristics in individual patients.
On the basis of a T1 map, a mask comprising pixels with T1 values characteristic for GM is created from which the local cortical extent (CE) is determined. The local smoothness (SM) of the GM‐WM junctions is derived from the T1 gradient. For display of cortical malformations, the resulting CE and SM maps serve to enhance local intensities in synthetic double inversion recovery (DIR) images calculated from the T1 map.
The resulting CE‐ and/or SM‐enhanced DIR images appear hyperintense at the site of cortical malformations, thus facilitating FCD detection in epilepsy patients. However, false positives may arise in areas with naturally elevated CE and/or SM, such as large GM structures and perivascular spaces.
In summary, the proposed method facilitates the detection of cortical abnormalities such as cortical thickening and blurring of the GM‐WM junction which are typical FCD markers. Still, subject motion artifacts, perivascular spaces, and large normal GM structures may also yield signal hyperintensity in the enhanced synthetic DIR images, requiring careful comparison with clinical MR images by an experienced neuroradiologist to exclude false positives.
Regorafenib CSF penetration, efficacy, and MRI patterns in recurrent malignant glioma patients
(2019)
(1) Background: The phase 2 Regorafenib in Relapsed Glioblastoma (REGOMA) trial indicated a survival benefit for patients with first recurrence of a glioblastoma when treated with the multikinase inhibitor regorafenib (REG) instead of lomustine. The aim of this retrospective study was to investigate REG penetration to cerebrospinal fluid (CSF), treatment efficacy, and effects on magnetic resonance imaging (MRI) in patients with recurrent high-grade gliomas.
(2) Methods: Patients were characterized by histology, adverse events, steroid treatment, overall survival (OS), and MRI growth pattern. REG and its two active metabolites were quantified by liquid chromatography/tandem mass spectrometry in patients’ serum and CSF.
(3) Results: 21 patients mainly with IDH-wildtype glioblastomas who had been treated with REG were retrospectively identified. Thirteen CFS samples collected from 3 patients of the cohort were available for pharmacokinetic testing. CSF levels of REG and its metabolites were significantly lower than in serum. Follow-up MRI was available in 19 patients and showed progressive disease (PD) in all but 2 patients. Two distinct MRI patterns were identified: 7 patients showed classic PD with progression of contrast enhancing lesions, whereas 11 patients showed a T2-dominant MRI pattern characterized by a marked reduction of contrast enhancement. Median OS was significantly better in patients with a T2-dominant growth pattern (10 vs. 27 weeks respectively, p = 0.003). Diffusion restrictions were observed in 13 patients.
(4) Conclusion: REG and its metabolites were detectable in CSF. A distinct MRI pattern that might be associated with an improved OS was observed in half of the patient cohort. Treatment response in the total cohort was poor.
Simple Summary: Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques, such as amino acid PET imaging using the tracer O-(2-[18F]-fluoroethyl)-L-tyrosine (FET), expose features that have been shown to provide useful information to distinguish tumor progression from pseudoprogression. The usefulness of FET-PET in IDH-wildtype glioblastoma exclusively, however, has not been investigated so far. Recently, machine learning (ML) algorithms have been shown to offer great potential particularly when multiparametric data is available. In this preliminary study, a Linear Discriminant Analysis-based ML algorithm was deployed in a cohort of newly diagnosed IDH-wildtype glioblastoma patients (n = 44) and demonstrated a significantly better diagnostic performance than conventional ROC analysis. This preliminary study is the first to assess the performance of ML in FET-PET for diagnosing pseudoprogression exclusively in IDH-wildtype glioblastoma and demonstrates its potential.
Abstract: Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.
Purpose: Perfusion-weighted MRI (PWI) and O-(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) PET are both applied to discriminate tumor progression (TP) from treatment-related changes (TRC) in patients with suspected recurrent glioma. While the combination of both methods has been reported to improve the diagnostic accuracy, the performance of a sequential implementation has not been further investigated. Therefore, we retrospectively analyzed the diagnostic value of consecutive PWI and [18F]FET PET.
Methods: We evaluated 104 patients with WHO grade II–IV glioma and suspected TP on conventional MRI using PWI and dynamic [18F]FET PET. Leakage corrected maximum relative cerebral blood volumes (rCBVmax) were obtained from dynamic susceptibility contrast PWI. Furthermore, we calculated static (i.e., maximum tumor to brain ratios; TBRmax) and dynamic [18F]FET PET parameters (i.e., Slope). Definitive diagnoses were based on histopathology (n = 42) or clinico-radiological follow-up (n = 62). The diagnostic performance of PWI and [18F]FET PET parameters to differentiate TP from TRC was evaluated by analyzing receiver operating characteristic and area under the curve (AUC).
Results: Across all patients, the differentiation of TP from TRC using rCBVmax or [18F]FET PET parameters was moderate (AUC = 0.69–0.75; p < 0.01). A rCBVmax cutoff > 2.85 had a positive predictive value for TP of 100%, enabling a correct TP diagnosis in 44 patients. In the remaining 60 patients, combined static and dynamic [18F]FET PET parameters (TBRmax, Slope) correctly discriminated TP and TRC in a significant 78% of patients, increasing the overall accuracy to 87%. A subgroup analysis of isocitrate dehydrogenase (IDH) mutant tumors indicated a superior performance of PWI to [18F]FET PET (AUC = 0.8/< 0.62, p < 0.01/≥ 0.3).
Conclusion: While marked hyperperfusion on PWI indicated TP, [18F]FET PET proved beneficial to discriminate TP from TRC when PWI remained inconclusive. Thus, our results highlight the clinical value of sequential use of PWI and [18F]FET PET, allowing an economical use of diagnostic methods. The impact of an IDH mutation needs further investigation.
Ischemic lesion location based on the ASPECT score for risk assessment of neurogenic dysphagia
(2020)
Dysphagia is common in patients with middle cerebral artery (MCA) infarctions and associated with malnutrition, pneumonia, and mortality. Besides bedside screening tools, brain imaging findings may help to timely identify patients with swallowing disorders. We investigated whether the Alberta stroke program early CT score (ASPECTS) allows for the correlation of distinct ischemic lesion patterns with dysphagia. We prospectively examined 113 consecutive patients with acute MCA infarctions. Fiberoptic endoscopic evaluation of swallowing (FEES) was performed within 24 h after admission for validation of dysphagia. Brain imaging (CT or MRI) was rated for ischemic changes according to the ASPECT score. 62 patients (54.9%) had FEES-proven dysphagia. In left hemispheric strokes, the strongest associations between the ASPECTS sectors and dysphagia were found for the lentiform nucleus (odds ratio 0.113 [CI 0.028–0.433; p = 0.001), the insula (0.275 [0.102–0.742]; p = 0.011), and the frontal operculum (0.280 [CI 0.094–0.834]; p = 0.022). A combination of two or even all three of these sectors together increased relative dysphagia frequency up to 100%. For right hemispheric strokes, only non-significant associations were found which were strongest for the insula region. The distribution of early ischemic changes in the MCA territory according to ASPECTS may be used as risk indicator of neurogenic dysphagia in MCA infarction, particularly when the left hemisphere is affected. However, due to the exploratory nature of this research, external validation studies of these findings are warranted in future.
Linking epigenetic signature and metabolic phenotype in IDH mutant and IDH wildtype diffuse glioma
(2020)
Aims: Changes in metabolism are known to contribute to tumour phenotypes. If and how metabolic alterations in brain tumours contribute to patient outcome is still poorly understood. Epigenetics impact metabolism and mitochondrial function. The aim of this study is a characterisation of metabolic features in molecular subgroups of isocitrate dehydrogenase mutant (IDHmut) and isocitrate dehydrogenase wildtype (IDHwt) gliomas. Methods: We employed DNA methylation pattern analyses with a special focus on metabolic genes, large-scale metabolism panel immunohistochemistry (IHC), qPCR-based determination of mitochondrial DNA copy number and immune cell content using IHC and deconvolution of DNA methylation data. We analysed molecularly characterised gliomas (n = 57) for in depth DNA methylation, a cohort of primary and recurrent gliomas (n = 22) for mitochondrial copy number and validated these results in a large glioma cohort (n = 293). Finally, we investigated the potential of metabolic markers in Bevacizumab (Bev)-treated gliomas (n = 29). Results: DNA methylation patterns of metabolic genes successfully distinguished the molecular subtypes of IDHmut and IDHwt gliomas. Promoter methylation of lactate dehydrogenase A negatively correlated with protein expression and was associated with IDHmut gliomas. Mitochondrial DNA copy number was increased in IDHmut tumours and did not change in recurrent tumours. Hierarchical clustering based on metabolism panel IHC revealed distinct subclasses of IDHmut and IDHwt gliomas with an impact on patient outcome. Further quantification of these markers allowed for the prediction of survival under anti-angiogenic therapy. Conclusion: A mitochondrial signature was associated with increased survival in all analyses, which could indicate tumour subgroups with specific metabolic vulnerabilities.
Purpose: To investigate cortical thickness and cortical quantitative T2 values as imaging markers of microstructural tissue damage in patients with unilateral high-grade internal carotid artery occlusive disease (ICAOD).
Methods: A total of 22 patients with ≥70% stenosis (mean age 64.8 years) and 20 older healthy control subjects (mean age 70.8 years) underwent structural magnetic resonance imaging (MRI) and high-resolution quantitative (q)T2 mapping. Generalized linear mixed models (GLMM) controlling for age and white matter lesion volume were employed to investigate the effect of ICAOD on imaging parameters of cortical microstructural integrity in multivariate analyses.
Results: There was a significant main effect (p < 0.05) of the group (patients/controls) on both cortical thickness and cortical qT2 values with cortical thinning and increased cortical qT2 in patients compared to controls, irrespective of the hemisphere. The presence of upstream carotid stenosis had a significant main effect on cortical qT2 values (p = 0.01) leading to increased qT2 in the poststenotic hemisphere, which was not found for cortical thickness. The GLMM showed that in general cortical thickness was decreased and cortical qT2 values were increased with increasing age (p < 0.05).
Conclusion: Unilateral high-grade carotid occlusive disease is associated with widespread cortical thinning and prolongation of cortical qT2, presumably reflecting hypoperfusion-related microstructural cortical damage similar to accelerated aging of the cerebral cortex. Cortical thinning and increase of cortical qT2 seem to reflect different aspects and different pathophysiological states of cortical degeneration. Quantitative T2 mapping might be a sensitive imaging biomarker for early cortical microstructural damage.
Simple Summary: Targeted therapies are of growing interest to physicians in cancer treatment. These drugs target specific genes and proteins involved in the growth and survival of cancer cells. Brain tumor therapy is complicated by the fact that not all drugs can penetrate the blood brain barrier and reach their target. We explored the non-invasive method, Magnetic Resonance Spectroscopy, for monitoring drug penetration and its effects in live animals bearing brain tumors. We were able to show the presence of the investigated drug in mouse brains and its on-target activity.
Abstract: Background: BAY1436032 is a fluorine-containing inhibitor of the R132X-mutant isocitrate dehydrogenase (mIDH1). It inhibits the mIDH1-mediated production of 2-hydroxyglutarate (2-HG) in glioma cells. We investigated brain penetration of BAY1436032 and its effects using 1H/19F-Magnetic Resonance Spectroscopy (MRS). Methods: 19F-Nuclear Magnetic Resonance (NMR) Spectroscopy was conducted on serum samples from patients treated with BAY1436032 (NCT02746081 trial) in order to analyze 19F spectroscopic signal patterns and concentration-time dynamics of protein-bound inhibitor to facilitate their identification in vivo MRS experiments. Hereafter, 30 mice were implanted with three glioma cell lines (LNT-229, LNT-229 IDH1-R132H, GL261). Mice bearing the IDH-mutated glioma cells received 5 days of treatment with BAY1436032 between baseline and follow-up 1H/19F-MRS scan. All other animals underwent a single scan after BAY1436032 administration. Mouse brains were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Results: Evaluation of 1H-MRS data showed a decrease in 2-HG/total creatinine (tCr) ratios from the baseline to post-treatment scans in the mIDH1 murine model. Whole brain concentration of BAY1436032, as determined by 19F-MRS, was similar to total brain tissue concentration determined by Liquid Chromatography with tandem mass spectrometry (LC-MS/MS), with a signal loss due to protein binding. Intratumoral drug concentration, as determined by LC-MS/MS, was not statistically different in models with or without R132X-mutant IDH1 expression. Conclusions: Non-invasive monitoring of mIDH1 inhibition by BAY1436032 in mIDH1 gliomas is feasible.